报告：What can we learn about credit risk from debt valuation adjustments?
摘要： Motivated by the debate about the introduction of the fair value option for (financial) liabilities (FVOL) and the requirement to recognize and separately disclose in financial statements debt valuation adjustments (DVAs), this study explores what we can learn about a firm’s credit risk from DVAs. Using a sample of US bank holding companies that elect the FVOL, we show that DVAs generally cannot be explained by the same factors that explain contemporaneous changes in bank’s credit quality. We further find that DVAs can explain future changes in credit risk when the fair value of liabilities is based on managerial inputs (Level 3). Overall, our results suggest that managers have an information advantage in estimating credit risk and that DVAs provide inside information to the market.
报告人简介：林雯博士现任英国兰卡斯特大学会计学助理教授。2019年博士毕业于英国兰卡斯特大学金融和会计专业。研究方向为银行、结构化信用风险模型、资本市场、信息披露。研究论文接受发表于Review of Accounting Studies。讲授财务报表分析，会计信息系统以及财务导论本科课程。
报告：Post-Earnings Announcement Drift: An Event Study Analysis
摘要：The documentation of post-earnings announcement drift (PEAD) by Ball and Brown (1968), has been extensively researched in the following 50 years. Perhaps the most widely cited explanation for this drift is a claim of investors’ under-reaction to the earnings announcement. However, most of the prior analyses look at PEAD from the perspective of trading strategy, that is, whether a buy and-hold strategy makes excess returns over a benchmark portfolio, most commonly, the market portfolio. This paper will look at the PEAD from an event study perspective, that is, to see if the realization of unexpected earnings (event), actually changes the returns process. My findings suggest that there is no post-earnings-announcement drift if this phenomenon is viewed as a systematic change in the returns process post-earnings announcement relative to the returns process in the pre-earnings announcement window for portfolios formed using SUE (standardized unexpected earnings) deciles on the date of the earnings announcement.